论文标题
比特率约束点云压缩的速率延伸建模
Rate-Distortion Modeling for Bit Rate Constrained Point Cloud Compression
论文作者
论文摘要
作为3D现实世界的主要代表形式之一，非常适合虚拟现实和增强现实应用，Point Clouds已获得了很多知名度。为了减少大量数据，已经进行了大量有关点云压缩的研究。但是，给定目标比特率，如何正确选择压缩点云的颜色和几何量化参数仍然是一个开放的问题。在本文中，我们为比特率约束点云压缩提出了基于速率模型的量化量化参数选择方案。首先，为了克服评估点云失真的测量不确定性，我们提出了一个统一模型，以结合几何变形和颜色失真。在此模型中，我们考虑了点云的几何变量与颜色变量之间的相关性，并得出无量纲数量以表示整体质量降解。然后，我们得出了总体失真和比特率与量化参数的关系。最后，我们使用派生的多项式模型将比特率约束点云压缩作为约束最小化问题，并通过迭代数值方法推导解决方案。实验结果表明，所提出的算法可以在各种目标比率下实现最佳的解码点云质量，并且基于视频速率 - 距离模型基于点云压缩方案的表现显着胜过。
As being one of the main representation formats of 3D real world and well-suited for virtual reality and augmented reality applications, point clouds have gained a lot of popularity. In order to reduce the huge amount of data, a considerable amount of research on point cloud compression has been done. However, given a target bit rate, how to properly choose the color and geometry quantization parameters for compressing point clouds is still an open issue. In this paper, we propose a rate-distortion model based quantization parameter selection scheme for bit rate constrained point cloud compression. Firstly, to overcome the measurement uncertainty in evaluating the distortion of the point clouds, we propose a unified model to combine the geometry distortion and color distortion. In this model, we take into account the correlation between geometry and color variables of point clouds and derive a dimensionless quantity to represent the overall quality degradation. Then, we derive the relationships of overall distortion and bit rate with the quantization parameters. Finally, we formulate the bit rate constrained point cloud compression as a constrained minimization problem using the derived polynomial models and deduce the solution via an iterative numerical method. Experimental results show that the proposed algorithm can achieve optimal decoded point cloud quality at various target bit rates, and substantially outperform the video-rate-distortion model based point cloud compression scheme.
